Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification

Abstract

Background Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. Methods In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%. Results Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. Conclusions Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.

Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?

“…As the Gail model only considers first-degree relatives and ignores age at disease onset, the estimated risk may be underestimated risk in half of the families with cancer on the father's side of the family [41,43,44]. Gao et al showed in the same dataset that the performance of the Gail model in estimating 5-year absolute risk improved with the use of Singaporean race-specific invasive breast cancer rates and mortality rates for deaths not due to breast cancer [41,45]. With a longer follow-up time, we were able to extend the work to explore absolute risk predictions for longer time horizons.…”

The Doctor Will Talk to You Now: A Discussion on Personalised Breast Cancer Risk in the Clinic

“…[7][8][9] Studies have shown that a combination of different risk assessment tools, both genetic and non-genetic, can be valuable in identifying women at high risk of breast cancer. 10,11 Ho et al explored how different risk factors, including family history, genetic predisposition, and non-genetic factors, can be used to stratify women's individual risk of developing breast cancer. 10,11 Results from the analysis involving 7,600 Asian breast cancer patients aged 30 to 75 highlight that each type of risk predictor independently identifies women at high risk of breast cancer.…”

“…10,11 Ho et al explored how different risk factors, including family history, genetic predisposition, and non-genetic factors, can be used to stratify women's individual risk of developing breast cancer. 10,11 Results from the analysis involving 7,600 Asian breast cancer patients aged 30 to 75 highlight that each type of risk predictor independently identifies women at high risk of breast cancer. The overlap of high-risk women identified did not show a high degree of overlap.…”

Functions and mechanisms of RNA m6A regulators in breast cancer (Review)

“…Familial inheritance is another universally acknowledged formidable hazard factor for BC. Women with a family history have a 2-to-4-fold increased probability of suffering from BC compared to others, with younger diagnosis ages and even higher mortality rates (24,25). Germline mutations in genes such as ATM serine/threonine kinase, BRCA1 DNA repair associated (BRCA1), BRCA2, checkpoint kinase 2 and partner and localizer of BRCA2 are frequently associated with an increased risk of developing BC (26,27).…”